This invention relates in general to the measurement of moisture, i.e., water vapor or dew point in a gas, and more particularly to such measurement using a compact solid state sensor which provides rapid measurement of absolute humidity or dew point over a wide range of temperature and pressure conditions.
The technique for performing a measurement of this sort has evolved, from the nineteenth century approach of plotting the temperature differential between dry and wet bulb thermometers, to modem systems wherein a small well-defined circuit element or structure which changes its resistance or capacitance in response to the surrounding humidity, is adapted to sense humidity in diverse process or measurement environments. By making the active circuit element thin or small, one is able to provide an instrument which reaches equilibrium with the atmosphere relatively quickly, and by utilizing films of material such as polymer or ceramic, these instruments may be relatively long-lived, such-that the compilation of a table of operating parameters is readily carried out and can remain in effect or be recalibrated to achieve accuracy, or at least repeatability, for extended periods of time.
One example of this approach to humidity sensing instrumentation is shown in U.S. Pat. No. 3,523,244. That patent shows a sensor element in which an aluminum oxide layer approximately one quarter of a micron thick is formed on a conductive substrate and covered with a thin conductive but porous top surface electrode. The oxide layer, a hard hydrated form of aluminum oxide with an irregular pore structure, allows water vapor to permeate or diffuse through its thickness. This material takes on water in proportion to its partial pressure in the surrounding atmosphere, and changes in both its resistance and its capacitance are readily measured between the substrate and the surface electrode. As noted above, because of the relatively small thickness of the active layer, the element responds quickly to the surrounding humidity, with a response time normally ranging from a fraction of second to several minutes, depending on degree of saturation, and has a wide range for humidity levels that change over a range of several orders of magnitude.
Readout of such a device is accomplished with conventional circuitry of the type used for a great number of capacitive or resistive sensors, such as load cells, diaphragm-type capacitive differential pressure measuring instruments, and others. This may be done with a capacitance measuring bridge, or other such circuit. For example, a square or sawtooth wave oscillation of a few hundred to a few thousand Hz may be provided across the element to cyclically charge and discharge the sensor, and the voltage developed on the sensor may be synchronously sampled, amplified, rectified, and output as a normalized (e.g., zero to one volt) signal. In various embodiments, the direct voltage readout may be strictly proportional to absolute humidity or otherwise reflect the humidity reading in a particularly simple fashion. More generally, the capacitance will vary both with humidity and with temperature of the element, and readout is accomplished by having first compiled a table of the output values, and stored the table, and then applying the correct calibration scale from the stored table for the given temperature, pressure or other directly measured condition.
In addition to hydrated ceramic films as described in the above-referenced '244 patent, a number of films of a polymer, such as a polysulphone or other material, have been used as the water-sensitive layer to enhance the response, stability or other characteristics of the sensor.
One method for using such sensors is to first obtain a sensor calibration curve of the sensor capacitance for each relative humidity at fixed temperature. The calibration curves are stored. Then, when a sensor is used in the field, a sample gas with an unknown relative humidity or dew point is applied to the sensor. The corresponding capacitance value is measured, the unknown relative humidity can be found by finding the corresponding value on the previously compiled capacitance versus relative humidity calibration curve. When the relative humidity and sensor temperature are both known, the corresponding dew point is also uniquely determined and may be found or interpolated empirically from widely available tables of saturated water vapor pressure versus temperature. However, since the sensor is in general quite small, the above methodology implicitly measures the sensor capacitance or resistance at the temperature of the test gas, and this requires that the calibration curve be obtained and stored for all temperature levels at which the element is to be used. Other measures of moisture content may be used for the initial calibration or the subsequent measurements.
While in theory this measurement can be made quite accurate, in practice, a number of possible sources of error are inherent in the methodology. First, any temperature detection error leads to reliance on an inappropriate calibration curve. Second, as a practical matter calibration curves are compiled at the time the sensor is built or installed, so that sensor "aging" over time may cause its characteristics to depart from those originally measured. Third, some hysteresis error may arise because the process of detection relies on the absorption or desorption of water from the thin layer, and the driving forces for the mechanics of equilibration may be affected by the previous level of humidity measured, so that the current measurement reading will depend on the previous relative humidity and the time interval during which the new and different level has been applied to the sensor. This memory effect may last for days or weeks. Furthermore, systematic errors of the measuring instrument such as errors in capacitance measuring bridges, in volt meters, parasitic capacitance of connecting cables, or changes in capacitance due to bending or realignment of wires, or changes in other circuit parameters that occur with temperature, may all contribute to inaccuracies of the fundamental signals or of their conversion to humidity measurements.
A number of these sources of error can be overcome in a sophisticated measurement environment by processes of recalibrating or reinstalling the equipment, protocols for baking out or zeroing the sensor, and by initializing or purging processes such as applying a reference dry gas for a known period of time, or other processes which may be specific to the sensor or electronics under consideration. Furthermore when operated with a microprocessor-controlled circuit, as is commonly done, tables of normal aging characteristics may be built into the device, allowing an estimated correction factor to be applied for some of these effects. However, a standard correction protocol, even one involving a constant offset plus a linear term, can only be expected to achieve accuracy in the middle range of moisture parameter values, e.g., 1-95% RH. For the measurement of trace moisture levels, where equlibrium is achieved slowly and the effects of drift and slow processes occur, little or no improvement may be obtained by simple or formulaic updating of the original calibration table.
Theoretically, this may be understood as follows. The commonly used or conventional capacitance versus moisture calibration curve can be represented by the formula EQU C=C.sub.o +F(moisture) (1)
Classical sensor sensitivity is .DELTA.F/.DELTA.(moisture), with a typical value of about 0.4 pF/% RH, while the moisture content of the gas may be expressed in any appropriate units of choice (partial pressure, RH, Dew/Frost Point, etc.). Both C.sub.o and F(moisture) can be found by the experimental procedure commonly followed for initial sensor calibration, i.e., by placing the sensor in a series of known humidity gas environments and measuring the characteristics, tabulating and storing the results. Subsequently, by measuring sensor capacitance C, one can find EQU F(moisture)=C-C.sub.o (1')
and thus, the moisture content itself.
However, it is well known that C.sub.o and F(moisture) retain their initial values only for relatively short period of time after calibration. Because of variety of reasons such as sensor "aging", failure to fulfill equilibrium conditions, "memory" effects from the preceding environment, stray capacitance changes, and the like, C.sub.0 and F(moisture) gradually deviate from their initial values. Thus, after some time "true" calibration curve or actual current response will have the form EQU C=(C.sub.o +.delta.C.sub.o)+F(moisture)*.alpha.
where .delta.C.sub.o is a function of time, which is commonly known as the zero drift.
The coefficient a represents the calibration curve "slope" and can be reasonably assumed equal 1 for a relatively long period of time, e.g. several months or longer. This assumption is based on experimental data, at least in a clean background gas environment, and as a practical matter does not introduce additional error in the typical low-end measurement range, below 5% RH.
At the time of measurement, the moisture content can then be found by the formula EQU F(moisture)=C-(C.sub.o +.delta.C.sub.o) (2)
Unfortunately, .delta.C.sub.o is not generally known, unless the sensor has been recently re-calibrated. The common solution is to substitute for (C.sub.o +.delta.C.sub.o) in equation (2), at the time a measurement is made, simply the original C.sub.o found at the time of initial calibration. This will give an uncertainty of .+-..delta.C.sub.o in the resulting F(moisture) value, and results in a moisture measurement error typically from 0.5% to 2% RH.
It is possible to improve measurement accuracy by using an in situ recalibration using an analytical model and an abbreviated set of measurements, such as several capacitance measurements at different temperatures with at least one "absolute" measurement of 100% RH obtained by cooling the sensor to the dew point or frost point. These data points are then used to update the current values of C.sub.o as well as sensor sensitivity, and thus update the stored calibration curve. One such approach is shown in U.S. Pat. No. 5,033,284, which reports a method using a heated or cooled sensor for obtaining the required data points. As a practical matter, corrections of this sort are adequate when the sensor is used in a mid-range of RH measurement values from few % to 100% RH. It relies on the fact that temperature change at constant water partial pressure can be used to simulate water pressure change at constant temperature.
Several limitations, however, do not allow this method to be extended to very low moisture ranges, for example to measurements of gas Frost point below about -40.degree. C. and RH below about 0.5%. In addition to the above-mentioned requirement that one of the temperature data points be as low as the Frost Point, the analytic models used for calculation to update the calibration curves do not take into account the particular properties of the individual sensor. For instance, the calibration curve's coefficients C.sub.o and .alpha. are implicitly assumed to be independent of temperature. However, in practice, the coefficient C.sub.o exhibits a temperature drift equivalent to at least 0.01% RH per .degree. C., and a more typical average value of this quantity is 0.05% to 0.2% per .degree. C. for temperatures T&lt;23.degree. C. Since the new data points themselves require a temperature change of many tens of degrees Celsius, this factor alone yields a calibration curve error at least .about.0.5% RH. In addition, any series used to represent a real calibration curve should be limited to a few first terms, and for accuracy, it is necessary to establish sensor-moisture equilibrium at each temperature point during calibration and when taking moisture measurements as well. These conditions severely limit the range and utility of such corrections.
Overall it may be said that the development of solid state humidity sensors and associated instrumentation have led to relatively hardy and compact embodiments of sensors capable of making repeated measurements, but these measurements, because of the underlying physics of the sensor and electrical signal processing, possess limitations that should be addressed.
It would therefore be desirable to provide a humidity sensor of enhanced accuracy, stability or ease of calibration.